CN103533613B - A kind of amplification forwarding relay selection method under out-of-date channel information - Google Patents

Abstract

The invention discloses the relay selection method under a kind of out-of-date channel information, feature be underway continue selection time, source node obtains the out-of-date signal-tonoise information of the first hop link by feedback, and utilize channel correlation coefficient for auxiliary, calculate and the condition break-point probability of relatively more each relaying correspondence, then select the relaying making this outage probability minimum as cooperating relay.Compared to traditional relay selection scheme only relying on signal-tonoise information, owing to considering channel relevancy, improve the reliability of relay selection, the present invention has higher robustness to channel time delay, it is possible to improve systematic function significantly.

Description

Amplifying forwarding relay selection method under outdated channel information

Technical Field

The invention belongs to the technical field of wireless communication relays, and particularly relates to an amplification forwarding relay selection method for performing relay selection by adopting outdated channel information.

Background

The cooperative communication system adopting the relay can effectively improve the coverage area and the system capacity, and is beneficial to solving the problems that the requirements of cell edge users in the traditional cellular cell cannot be met and the data transmission rate is small. The relay selection technology can effectively reduce the complexity of the system and simultaneously ensure higher diversity gain of the system. In a conventional relay selection algorithm, a node needs to calculate a link signal-to-noise ratio corresponding to each relay according to feedback channel state information, and select a relay with the largest signal-to-noise ratio for cooperative transmission. In an actual system, due to feedback delay, the node uses outdated channel state information, which is different from an actual channel, so that relay selection reliability is reduced, and system performance is reduced.

Through the search of the existing documents, the article "amplified forwarding Relay Selection based on Partial channel information" (ieee commu.lett., vol.12, No.4, pp.235-237,2008) proposes a Partial Relay Selection (PRS) scheme based on Partial channel information, but considers the Relay Selection under the complete channel information and does not consider the influence of the outdated channel information on the Relay Selection. The article of relay selection performance analysis based on partial channel information in a scene with channel delay (IEEE Signal process.lett., vol.17, No.6, pp.531-534,2010) analyzes the negative influence of outdated channel information on the PRS scheme, but does not propose a further improvement scheme to compensate for the performance loss caused by the outdated channel information. Although a decoding forwarding relay selection scheme based on channel statistical information and channel correlation as assistance, which is proposed in the design of relay selection scheme adopting outdated channel information in a renewable cooperative network (IEEE trans. wireless Commun., vol.10, No.9, pp.3086-3097,2011), can effectively make up for the performance loss caused by outdated channel information, the signal forwarding mechanism and the relay selection mechanism of decoding, amplifying, forwarding relay and amplifying forwarding relay are different, so the scheme is not suitable for amplifying, forwarding relay selection.

The invention content is as follows:

the invention aims to provide an amplifying and forwarding relay selection method under outdated channel information, which is suitable for relay selection of an amplifying and forwarding relay system of single-source, multi-relay and monocular nodes under a scene with feedback delay, solves the problem of inaccurate relay selection caused by outdated channel information and achieves the aim of improving the system performance.

The invention relates to an amplifying forwarding relay selection method under outdated channel information, which comprises the following steps: in a cooperative network with a single source, a single destination node and multiple relays, a communication process is completed in two time slots, and in the first time slot, the source node selects one relay according to feedback information and sends a data packet to the relay; in the second time slot, the selected relay node forwards the data packet to the destination node in an amplifying and forwarding mode to complete communication; the method is characterized in that: when relay selection is carried out, after the source node obtains outdated signal-to-noise ratio information of a first hop link through feedback, the conditional interruption probability corresponding to each relay is calculated and compared by taking a channel correlation coefficient as assistance, and then the relay with the minimum interruption probability is selected as a cooperative relay; the specific operation steps are as follows:

the first step is as follows: the system is initialized, the source node obtains the position information of each node, and the distance d from the source node to the relay node and the distance d from the relay node to the destination node are calculated_1(i)And d_2(i)(ii) a Then calculating the large-scale fading of each link: and average signal-to-noise ratio:where subscripts 1 and 2 denote a first hop link from the source node to the relay node and a second hop link from the relay node to the destination node, i ∈ [1, N_r]Denotes a relay number, N_rRepresenting optional total number of relays, E {. The } representing the get desired operator, α representing the path loss factor, P_SIs the transmission power of the source node, P_rFor the transmission power of the relay node, N₀₁、N₀₂The power of additive white Gaussian noise of the first hop link and the second hop link;

the second step is that: a source node sends a relay selection starting command;

the third step: after each relay node receives the starting command, channel information of each first hop link, namely the link from the source node to the relay node, is obtainedAnd measuring the Doppler shift f_d(i)Then feeding back the information to the source node;

the fourth step: calculating the interruption probability corresponding to each relay: after obtaining the Doppler frequency shift and the channel information parameters, the source node calculates the channel correlation coefficient rho of the first hop link_1(i)＝J₀(2πf_d(i)τ) and signal-to-noise ratioWherein, J₀(. h) is a first class zero order Bessel function, and τ is channel delay; then, the conditional interruption probability corresponding to each relay is calculated according to the informationThe conditional interruption probability is calculated by the following formula:

$\begin{array}{c}{P}_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=\underset{m=0}{\overset{\mathrm{\∞}}{\Σ}}\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\{\mathrm{\Γ}(m+1)-\frac{2e^{\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\left){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\}\end{array}$

wherein, γ₀Representing the signal-to-noise threshold, η_1(i)Representing the average signal-to-noise ratio of the first hop link, η_2(i)Representing the average signal-to-noise ratio of the second hop link,is a parameter related to the average signal-to-noise ratio of the first hop link, (. cndot.) represents a gamma function, K_v(. h) represents a modified Bessel function of order v of the first type;

the fifth step: the source node compares the interruption probability corresponding to each relay node, selects the relay node with the minimum value as the cooperative relay, and records the relay node as the cooperative relayThe specific calculation process is as follows:

initializationThe iteration number m is 0;

updating according to formula of conditional interruption probability

Calculation formula according to conditional interruption probability iteration increment

$\begin{array}{c}{B}_{m,i}=\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\×\{\mathrm{\Γ}(m+1)-\frac{2e^{-\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\left){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\},\end{array}$

Computing conditional outage probability iteration increment B_m,i；

Updating the formula according to the conditional interruption probabilityUpdating

If it isUpdating m to m +1, and jumping to a calculation formula updating step according to the conditional interruption probability; otherwise, ending the circulation;

selecting the relay node which minimizes the interruption probability, wherein the relay index is marked as k,

and a sixth step: the node notifies the selected relay node k, data is sent to the relay node, and other relay nodes keep a standby state;

the seventh step: after receiving the data, the relay node k performs amplification forwarding on the data to the destination node, and assists the source node to complete data transmission.

The invention provides a new relay selection algorithm in an amplifying and forwarding relay system under the condition of existence of feedback time delay from the perspective of minimizing the interruption probability. Compared with the traditional method which only depends on the signal-to-noise ratio information of the outdated channel to select the relay, the method adds the cross-correlation information between the actual channel and the outdated channel to assist, and selects the interruption probability as the standard of relay selection; because the channel correlation is considered, the reliability of relay selection is improved, the method has stronger robustness to channel delay, and the system performance can be obviously improved.

Drawings

Fig. 1 is a block diagram of a wireless multi-relay communication system to which the method for selecting an amplify-and-forward relay according to outdated channel information of the present invention is applied;

fig. 2 is a relay selection flow chart proposed by the amplify-and-forward relay selection method under the outdated channel information of the present invention.

Fig. 3 is a graph comparing the interrupt probability performance of the method of the present invention with that of the conventional method when the channel cross-correlation coefficient is 0.3.

Fig. 4 is a graph comparing the interrupt probability performance of the method of the present invention with that of the conventional method under different channel cross-correlation coefficients.

Fig. 5 is a graph comparing error rate performance of the method of the present invention and the conventional method when QPSK modulation is used and the channel cross-correlation coefficient is 0.3.

Fig. 6 is a graph comparing error rate performance of the method of the present invention and the conventional method when 16QAM modulation is used and the channel cross-correlation coefficient is 0.3.

Detailed Description

The invention is described in further detail below with reference to the figures and examples.

Example 1:

fig. 1 is a block diagram of a wireless multi-relay communication system to which the method for selecting an amplify-and-forward relay under outdated channel information is applied. As shown in fig. 1: the method is applicable to a wireless communication network consisting of a single source node, a single destination node and a plurality of relay nodes. Each node is configured with a single antenna, and the number of relays is set as N_r. The communication process can be divided into two phases: in the first phase, the source node S sends a signal to the selected relay node R_(k)Transmitting dataIn the second stage, the relay node R_(k)Amplifying and forwarding data to destination nodeWherein h is_1(k)、h_2(k)Respectively representing a source node S to a relay node R_(k)Relay node R_(k)Small-scale rayleigh fading to the destination node D; lambda [ alpha ]_1(k)、λ_2(k)Represents the large scale fading of the channel, i.e., the average gain of the channel; n is_1(k)、n_2(k)Is at a power of N₀₁、N₀₂Additive white gaussian noise of (1); g is an amplification forwarding coefficient; p_SIs the transmission power of the source node, P_rIs the transmit power of the relay node; in the figure, γ_1(i)、γ_2(i)Representing the actual channel signal-to-noise ratio;represents the outdated channel signal-to-noise ratio information used by the source node for relay selection, is gamma_1(i)An outdated version of (a). In this embodiment, the relay number N is taken_r＝3。

Fig. 2 is a flow chart illustrating the operation of the method for selecting an amplify-and-forward relay suitable for the outdated channel information of the present invention. As shown in fig. 2, the method for selecting an amplify-and-forward relay under outdated channel information of the present invention comprises the following steps:

(S1) the system is initialized, the source node obtains the position information of each node, and the distance d between the source node and the relay node and between the relay node and the destination node is calculated_1(i)And d_2(i)(ii) a Where subscripts 1 and 2 denote a first hop link (source node to relay node) and a second hop link (relay node to destination node), respectively, (i) denotes a relay label; calculating the large-scale fading of each link:and average signal-to-noise ratio: α denotes the path loss factor;

(S2) the source node transmitting a relay selection start command;

(S3) each relay node receives the starting command and then obtains the channel information of each first hop linkAnd measuring the Doppler shift f_d(i)Then feeding back the information to the source node;

(S4) calculating a probability of interruption for each relay: sourceAfter obtaining the Doppler frequency shift and the channel information parameters, the node calculates the channel correlation coefficient rho of the first hop link_1(i)＝J₀(2πf_d(i)τ) and signal-to-noise ratio Tau is the channel delay; then, the corresponding interruption probability of each relay is calculated according to the information, and the method further comprises the following specific steps:

(41) source node is at N_rSelecting one relay from the selectable relay nodes to participate in cooperation, and assuming that the selected relay is the relay (i), a system end-to-end signal-to-noise ratio expression is as follows:

${\mathrm{\γ}}_{e2e}=\frac{{\mathrm{\γ}}_{1\left(i\right)}{\mathrm{\γ}}_{2\left(i\right)}}{C+{\mathrm{\γ}}_{2\left(i\right)}}---\left(1\right)$

whereinIs a parameter related to the average signal-to-noise ratio of the first hop link;

(42) after obtaining the link channel information, the source node selects a system interrupt probability expression when the relay (i) performs cooperative transmission:

$\begin{array}{c}{P}_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=\mathrm{Pr}({\mathrm{\γ}}_{e2e}\≤{\mathrm{\γ}}_0|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})\\ ={\∫}_{x=0}^{+\mathrm{\∞}}{f}_{{\mathrm{\γ}}_{1\left(i\right)}|{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}\left(x\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})dx-{\∫}_{x={\mathrm{\γ}}_0}^{+\mathrm{\∞}}(1-F_{{\mathrm{\γ}}_{2\left(i\right)}}(\frac{{\mathrm{C\γ}}_0}{(x-{\mathrm{\γ}}_0)}\left)\right)\×f_{{\mathrm{\γ}}_{1\left(i\right)}|{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}\left(x\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})dx\end{array}---\left(2\right)$

wherein,for the first hop link actual signal-to-noise ratio gamma_1(i)When its outdated version is knownThe conditional probability density function of time is calculated as follows:

$f_{{\mathrm{\γ}}_{1\left(i\right)}|{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}\left(x\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=\frac{e^{-\frac{x+{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{I}_0\left(\frac{2\sqrt{{\mathrm{\ρ}}_{1\left(i\right)}^{2}x{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)---\left(3\right)$

for the second hop link actual signal-to-noise ratio gamma_2(i)The specific expression of the cumulative distribution function of (2) is as follows:

$F_{{\mathrm{\γ}}_{2\left(i\right)}}\left(z\right)=1-e^{-z/{\mathrm{\η}}_{2\left(i\right)}}---\left(4\right)$

(43) substituting the formula (3) and the formula (4) into the formula (2) to obtain a calculation formula of the interruption probability:

$\begin{array}{c}{P}_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=\underset{m=0}{\overset{\mathrm{\∞}}{\Σ}}\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\{\mathrm{\Γ}(m+1)-\frac{2e^{\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\left){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\}\end{array}---\left(5\right)$

(S5) selecting the relay node with the minimum interruption probability to participate in the cooperation, and specifically operating as follows:

(51) initializationThe iteration number m is 0;

(52) updating according to formula (5)

$\begin{array}{c}{B}_{m,i}=\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\×\{\mathrm{\Γ}(m+1)-\frac{2e^{-\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\left){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\}\end{array}---\left(6\right)$

$P_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=P_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})+B_{m,i}---\left(7\right)$

(53) If it isUpdating m to m +1, and jumping to (52) an updating interruption probability step; otherwise, ending the circulation;

(54) selecting the relay node which minimizes the interruption probability, wherein the relay label is marked as k:

$k=\underset{i}{min}\left\{P_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})\right\}---\left(8\right)$

(S6) the source node notifying the selected relay node k to transmit data to the relay node, and the other relay nodes remaining on standby;

(S7) after receiving the data, the relay node k amplifies and forwards the data to the destination node to assist the source node in completing the data transmission.

FIG. 3 is a simulation comparison result of the method of the present invention and the conventional SNR-based maximum method under a scenario of relay number 3, where the upper curve a3 and the lower curve b3 are performance simulation curves of the system outage probability varying with the SNR of the first hop link using the conventional method and the method of the present invention, respectively_1(i)＝η_2(i),i＝1,2,3，η₁₍₂₎＝η₁₍₃₎＝η₁₍₁₎-3dB, channel correlation coefficient p_1(i)0.3, i is 1,2, 3. As can be seen from FIG. 3, under the condition of the same signal-to-noise ratio, the interruption probability is smaller and the performance is better when the method of the invention is adopted compared with the traditional method. At a higher signal-to-noise ratio (>15dB) and the same interruption probability, the method has 2-3dB performance gain compared with the traditional method.

The simulation scenario setup in fig. 4 is the same as that in fig. 3, and the interrupt probability performance of the method of the present invention and the conventional method under different channel correlation coefficients is compared. Curves a4, b4, c4, d4, e4 and f4 in the figure are performance simulation curves of the conventional method and the method of the present scheme, wherein the interruption probability of the method varies with the signal-to-noise ratio of the first hop channel under different channel correlation coefficients; curves a4, b4 and c4 are interruption probability curves of the conventional method when the channel correlation coefficient is 0.1, 0.5 and 0.7 respectively; curves d4, e4, and f4 are interruption probability curves of the present method when the channel correlation coefficient is 0.1, 0.5, and 0.7, respectively. As can be seen from fig. 4, when the correlation coefficients are different, the method of the present invention has significantly improved interrupt probability performance compared to the conventional method, which shows that the method of the present invention has higher robustness to channel delay.

Fig. 5 and fig. 6 are graphs of average error rate performance of the method of the present invention and the conventional method in QPSK and 16QAM modulation modes, respectively. Curves a5 and b5 are performance curves of the error rate changing with the signal-to-noise ratio of the first hop link in the QPSK modulation mode by the traditional method and the method of the invention respectively; curves a6 and b6 are error codes of the traditional method and the method of the invention under the 16QAM modulation mode respectivelyPerformance Curve with Rate variation with first hop Link SNR in the simulation, Relay number is 3, and average SNR η_1(i)＝η_2(i),i＝1,2,3，η₁₍₂₎＝η₁₍₃₎＝η₁₍₁₎-5dB, channel correlation coefficient p_1(i)0.3, i is 1,2, 3. As can be seen from fig. 5 and 6, the error rate performance of the method of the present invention is also superior to that of the conventional method.

In the embodiment, the channel correlation information is used as assistance, the relay with the minimum interruption probability is selected for cooperative transmission, and simulation results of the interruption probability performance and the error rate performance under different modulation modes are displayed.

Claims (1)

1. An amplifying forwarding relay selection method under outdated channel information comprises the following steps: in a cooperative network with a single source, a single destination node and multiple relays, a communication process is completed in two time slots, and in the first time slot, the source node selects one relay according to feedback information and sends a data packet to the relay; in the second time slot, the selected relay node forwards the data packet to the destination node in an amplifying and forwarding mode to complete communication; the method is characterized in that: when relay selection is carried out, after the source node obtains outdated signal-to-noise ratio information of a first hop link through feedback, the conditional interruption probability corresponding to each relay is calculated and compared by taking a channel correlation coefficient as assistance, and then the relay with the minimum interruption probability is selected as a cooperative relay; the specific operation steps are as follows:

the first step is as follows: the system is initialized, the source node obtains the position information of each node, and the distance d from the source node to the relay node and the distance d from the relay node to the destination node are calculated_1(i)And d_2(i)(ii) a Then calculating the large-scale fading of each link: and average signal-to-noise ratio:where subscripts 1 and 2 denote a first hop link from the source node to the relay node and a second hop link from the relay node to the destination node, i ∈ [1, N_r]Denotes a relay number, N_rRepresenting optional total number of relays, E {. The } representing the get desired operator, α representing the path loss factor, P_SIs the transmission power of the source node, P_rFor the transmission power of the relay node, N₀₁、N₀₂The power of additive white Gaussian noise of the first hop link and the second hop link;

the second step is that: a source node sends a relay selection starting command;

the third step: after each relay node receives the starting command, channel information of each first hop link, namely the link from the source node to the relay node, is obtainedAnd measuring the Doppler shift f_d(i)Then feeding back the information to the source node;

the fourth step: calculating the interruption probability corresponding to each relay: after obtaining the Doppler frequency shift and the channel information parameters, the source node calculates the channel correlation coefficient rho of the first hop link_1(i)＝J₀(2πf_d(i)τ) and signal-to-noise ratioWherein, J₀(. -) represents a first class of zeroth order Bessel function, τ being the channel delay; then, the conditional interruption probability corresponding to each relay is calculated according to the informationThe conditional interruption probability is calculated by the following formula:

$\begin{array}{c}{P}_{out}\left({\mathrm{\γ}}_0\right|{\widehat{\mathrm{\γ}}}_{1\left(i\right)})=\underset{m=0}{\overset{\mathrm{\∞}}{\Σ}}\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\{\mathrm{\Γ}(m+1)-\frac{2e^{-\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\left(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\right){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\}\end{array}$

wherein, γ₀Representing the signal-to-noise threshold, η_1(i)Representing the average signal-to-noise ratio of the first hop link, η_2(i)Representing the average signal-to-noise ratio of the second hop link,is a parameter related to the average signal-to-noise ratio of the first hop link, (. cndot.) represents a gamma function, K_v(. h) represents a modified Bessel function of order v of the first type;

the fifth step: the source node compares the interruption probability corresponding to each relay node, selects the relay node with the minimum value as the cooperative relay, and records the relay node as the cooperative relayThe specific calculation process is as follows:

initializationThe iteration number m is 0;

updating according to formula of conditional interruption probability

Calculation formula according to conditional interruption probability iteration increment

$\begin{array}{c}{B}_{m,i}=\frac{e^{-\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{{(m!)}^2}{\left(\frac{{\mathrm{\ρ}}_{1\left(i\right)}^2{\widehat{\mathrm{\γ}}}_{1\left(i\right)}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\×\{\mathrm{\Γ}(m+1)-\frac{2e^{-\frac{{\mathrm{\γ}}_0}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}{\left(\frac{1}{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}\right)}^m\\ \×\underset{v=0}{\overset{m}{\Σ}}\[\left(\begin{array}{c}m\\ v\end{array}\right){\mathrm{\γ}}_0^{m-v}{\left(\frac{{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\left(1-{\mathrm{\ρ}}_{1\left(i\right)}^2\right){\mathrm{\η}}_{1\left(i\right)}\right)}^{\frac{1}{2}(v+1)}{K}_{v+1}\left({\left(\frac{4{\mathrm{C\γ}}_0}{{\mathrm{\η}}_{2\left(i\right)}}\right)}^{1/2}\frac{1}{\sqrt{(1-{\mathrm{\ρ}}_{1\left(i\right)}^2){\mathrm{\η}}_{1\left(i\right)}}}\right)\]\},\end{array}$

Computing conditional outage probability iteration increment B_m,i；

Updating the formula according to the conditional interruption probabilityUpdating

If it is1≤i≤N_rUpdating m to m +1, and jumping to a calculation formula updating step according to the conditional interruption probability; otherwise, ending the circulation;

selecting the relay node which minimizes the interruption probability, wherein the relay index is marked as k,

and a sixth step: the node notifies the selected relay node k, data is sent to the relay node, and other relay nodes keep a standby state;

the seventh step: after receiving the data, the relay node k performs amplification forwarding on the data to the destination node, and assists the source node to complete data transmission.